Australian Institute for Musculoskeletal Science (AIMSS), The University of Melbourne and Western Health, St. Albans, Victoria, Australia; Department of Medicine - Western Health, The University of Melbourne, St. Albans, Victoria, Australia.
Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Burwood, Victoria, Australia; Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Arch Gerontol Geriatr. 2023 Nov;114:105084. doi: 10.1016/j.archger.2023.105084. Epub 2023 May 30.
Different measures of muscle strength, physical performance and body size/composition are used in various sarcopenia definitions. This study investigated which baseline measures best predict incident mortality and falls, and prevalent slow walking speed in older women and men.
Data for 899 women (mean age±standard deviation, 68.7 ± 4.3 years) and 497 men (69.4 ± 3.9 years) from the Dubbo Osteoporosis Epidemiology Study 2, comprising sixty variables for muscle strength (quadriceps strength), physical performance (walking speed, timed up and go (TUG) test, sit to stand (STS) test), body size (weight, height, body mass index) and body composition (lean mass, body fat) were included. Sex-stratified Classification and Regression Tree (CART) analyses calculated baseline variable accuracy for predicting incident mortality and falls, and prevalent slow walking speed (<0.8 m/s).
Over 14.5 years, 103/899 (11.5%) women and 96/497 (19.3%) men died, 345/899 (38.4%) women and 172/497 (34.6%) men had ≥1 fall, and 304/860 (35.3%) women and 172/461 (31.7%) had baseline slow walking speed (<0.8 m/s). CART models identified age and walking speed adjusted for height as the most important predictors for mortality in women, and quadriceps strength (with adjustments) as the most important predictor for mortality in men. In both sexes, STS (with adjustments) was the most important predictor for incident falls, and TUG test was the most important predictor for prevalent slow walking speed. Body composition measures were not important predictors for any outcome.
Muscle strength and physical performance variables and cut points predict falls and mortality differently in women and men, suggesting targeted sex-specific application of selected measures may improve outcome prediction in older adults.
不同的肌肉力量、身体表现和身体大小/成分测量方法被用于各种肌少症定义中。本研究旨在探究哪些基线测量指标最能预测老年女性和男性的死亡率、跌倒事件和常见的步行速度缓慢。
纳入了来自 Dubbo 骨质疏松症流行病学研究 2 的 899 名女性（平均年龄±标准差，68.7±4.3 岁）和 497 名男性（69.4±3.9 岁）的数据，包含 60 个肌肉力量（股四头肌力量）、身体表现（步行速度、计时起立行走测试、坐站测试）、身体大小（体重、身高、体重指数）和身体成分（瘦体重、体脂肪）的指标。性别分层分类和回归树（CART）分析计算了预测死亡率、跌倒事件和常见步行速度缓慢（<0.8 m/s）的基线变量准确性。
在 14.5 年的随访期间，899 名女性中有 103 人（11.5%）死亡，497 名男性中有 96 人（19.3%）死亡；899 名女性中有 345 人（38.4%）跌倒≥1 次，497 名男性中有 172 人（34.6%）跌倒≥1 次；860 名女性中有 304 人（35.3%）、461 名男性中有 172 人（31.7%）基线步行速度缓慢（<0.8 m/s）。CART 模型确定年龄和身高调整后的步行速度是女性死亡率的最重要预测因素，而男性死亡率的最重要预测因素是股四头肌力量（经调整）。在男女两性中，坐站测试（经调整）是跌倒事件的最重要预测因素，计时起立行走测试是常见步行速度缓慢的最重要预测因素。身体成分测量指标不是任何结局的重要预测因素。
肌肉力量和身体表现变量及其切点在女性和男性中对跌倒和死亡率的预测作用不同，这提示有针对性地应用特定的测量指标可能会改善老年人群的结局预测。
